BackgroundSclerotinia Stem Rot (SSR), caused by the fungal pathogen Sclerotinia sclerotiorum, is ubiquitous in cooler climates where soybean crops are grown. Breeding for resistance to SSR remains challenging in crops like soybean, where no single gene provides strong resistance, but instead, multiple genes work together to provide partial resistance. In this study, a genome-wide association study (GWAS) was performed to dissect the complex genetic architecture of soybean quantitative resistance to SSR and to provide effective molecular markers that could be used in breeding programs. A collection of 420 soybean genotypes were selected based on either reports of resistance, or from one of three different breeding programs in Brazil, two commercial, one public. Plant genotype sensitivity to SSR was evaluated by the cut stem inoculation method, and lesion lengths were measured at 4 days post inoculation.ResultsGenotyping-by-sequencing was conducted to genotype the 420 soybean lines. The TASSEL 5 GBSv2 pipeline was used to call SNPs under optimized parameters, and with the extra step of trimming adapter sequences. After filtering missing data, heterozygosity, and minor allele frequency, a total of 11,811 SNPs and 275 soybean genotypes were obtained for association analyses. Using a threshold of FDR-adjusted p-values <0.1, the Compressed Mixed Linear Model (CMLM) with Genome Association and Prediction Integrated Tool (GAPIT), and the Fixed and Random Model Circulating Probability Unification (FarmCPU) methods, both approaches identified SNPs with significant association to disease response on chromosomes 1, 11, and 18. The CMLM also found significance on chromosome 19, whereas FarmCPU also identified significance on chromosomes 4, 9, and 16.ConclusionsThese similar and yet different results show that the computational methods used can impact SNP associations in soybean, a plant with a high degree of linkage disequilibrium, and in SSR resistance, a trait that has a complex genetic basis. A total of 125 genes were located within linkage disequilibrium of the three loci shared between the two models. Their annotations and gene expressions in previous studies of soybean infected with S. sclerotiorum were examined to narrow down the candidates.Electronic supplementary materialThe online version of this article (10.1186/s12864-017-4160-1) contains supplementary material, which is available to authorized users.

This study describes the muscle transcriptome profile of Bandur breed, a consumer favoured, meat type sheep of India. The transcriptome was compared to the less desirable, unregistered local sheep population, in order to understand the molecular factors related to muscle traits in Indian sheep breeds. Bandur sheep have tender muscles and higher backfat thickness than local sheep. The longissimus thoracis transcriptome profiles of Bandur and local sheep were obtained using RNA sequencing (RNA Seq). The animals were male, non-castrated, with uniform age and reared under similar environment, as well as management conditions. We could identify 568 significantly up-regulated and 538 significantly down-regulated genes in Bandur sheep (p≤0.05). Among these, 181 up-regulated and 142 down-regulated genes in Bandur sheep, with a fold change ≥1.5, were considered for further analysis. Significant Gene Ontology terms for the up-regulated dataset in Bandur sheep included transporter activity, substrate specific transmembrane, lipid and fatty acid binding. The down-regulated activities in Bandur sheep were mainly related to RNA degradation, regulation of ERK1 and ERK2 cascades and innate immune response. The MAPK signaling pathway, Adipocytokine signaling pathway and PPAR signaling pathway were enriched for Bandur sheep. The highly connected genes identified by network analysis were CNOT2 , CNOT6 , HSPB1 , HSPA6 , MAP3K14 and PPARD , which may be important regulators of energy metabolism, cellular stress and fatty acid metabolism in the skeletal muscles. These key genes affect the CCR4-NOT complex, PPAR and MAPK signaling pathways. The highly connected genes identified in this study, form interesting candidates for further research on muscle traits in Bandur sheep.

Recent changes in soybean management like the adoption of transgenic crops and no-till farming, in addition to the expansion of cultivated areas into new virgin frontiers, are some of the hypotheses that can explain the rise of secondary pests, such as the Neotropical brown stink bug, Euschistus heros, in Brazil. To better access the risk of increased pests like E. heros and to determine probabilities for insecticide resistance spreading, it is necessary first to access the levels of the genetic diversity, how the genetic diversity is distributed, and how natural selection is acting upon the natural variation. Using the genotyping by sequencing (GBS) technique, we generated ~60,000 single-nucleotide polymorphisms (SNPs) distributed across the E. heros genome to answer some of those questions. The SNP data was used to investigate the pattern of genetic structure, hybridization and natural selection of this emerging pest. We found that E. heros populations presented similar levels of genetic diversity with slightly higher values at several central locations in Brazil. Our results also showed strong genetic structure separating northern and southern Brazilian regions (FST = 0.22; p-value = 0.000) with a very distinct hybrid zone at the central region. The analyses also suggest the possibility that GABA channels and odorant receptors might play a role in the process of natural selection. At least one marker was associated with soybean and beans crops, but no association between allele frequency and cotton was found. We discuss the implications of these findings in the management of emerging pests in agriculture, particularly in the context of large areas of monoculture such as soybean and cotton.

Unravelling the details of range expansion and ecological dominance shifts of insect pests has been challenging due to the lack of basic knowledge about population structure, gene flow, and most importantly, how natural selection is affecting the adaptive process. Piezodous guildinii is an emerging pest of soybean in the southern region of the United States, and increasingly important in Brazil in recent years. However, the reasons P. guildinii is gradually becoming more of a problem are questions still mostly unanswered. Here, we have genotyped P. guildinii samples and discovered 1,337 loci containing 4,083 variant sites SNPs that were used to estimate genetic structure and to identify gene candidates under natural selection. Our results revealed the existence of a significant genetic structure separating populations according to their broad geographic origin, i.e., U.S. and Brazil, supported by AMOVA (FGT = 0.26), STRUCTURE, PCA, and FST analyses. High levels of gene flow or coancestry within groups (i.e., within countries) can be inferred from the data, and no spatial pattern was apparent at the finer scale in Brazil. Samples from different seasons show more heterogeneous compositions suggesting mixed ancestry and a more complex dynamic. Lastly, we were able to detect and successfully annotated 123 GBS loci (10.5%) under positive selection. The gene ontology (GO) analysis implicated candidate genes under selection with genome reorganization, neuropeptides, and energy mobilization. We discuss how these findings could be related to recent outbreaks and suggest how new efforts directed to better understand P. guildinii population dynamics.